Loanwords are the words transferred from one language to another, which become essential part of the borrowing language. The loanwords have come from the source language to the recipient language because of many reasons. Detecting these loanwords is complicated task due to that there are no standard specifications for transferring words between languages and hence low accuracy. This work tries to enhance this accuracy of detecting loanwords between Turkish and Arabic language as a case study. In this paper, the proposed system contributes to find all possible loanwords using any set of characters either alphabetically or randomly arranged. Then, it processes the distortion in the pronunciation, and solves the problem of the missing lette

Mental systems in ontological discourse turned into deliberative systems, derived from the non-coordinated thought that motivated ontological discourse, as an incomplete thought, after it became close to reason; Between creation and prevention, between reasoning and creation, between submission and ambition, the result of an interconnected entity that slays one another from one another, and intersects with one another, to produce a special pattern each time, completely different from its predecessor or to provide a path for the coordination of others, which is outside the linguistic event, or part From it, signs and marks, produced to a large extent M., and united the signs; to return again in a circular and rotational movement to produc

    Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accu

        This study highlights the problems of translating Shakespeare's food and drink-related insults (henceforth FDRIs) in (Henry IV, Parts I&II) into Arabic. It adopts (Vinay & Darbelnet's:1950s) model, namely (Direct& Oblique) to highlight the applicability of the different methods and procedures made by the two selected translators (Mashati:1990 & Habeeb:1905) .The present study tries to answer the following questions:(i) To what extent the FDRIs in Henry IV might pose a translational problem for the selected translators to find suitable cultural equivalents for them? (ii) Why do the translators, in many cases, resort to a literal procedure which is almost not worka

One of the primary problems in internet is security, mostly when computer utilization is increasing in all social and business areas. So, the secret communications through public and private channels are the major goal of researchers. Information hiding is one of methods to obtain a security communication medium and protecting the data during transmission.
This research offers in a new method using two levels to hide, the first level is hiding by embedding and addition but the second level is hiding by injection. The first level embeds a secret message in one bit in the LSB in the FFT and the addition of one kashida. Subtraction of two random images (STRI) is RNG to find positions for hiding within the text. The second level is the in

The purpose of this paper to discriminate between the poetic poems of each poet depending on the characteristics and attribute of the Arabic letters. Four categories used for the Arabic letters, letters frequency have been included in a multidimensional contingency table and each dimension has two or more levels, then contingency coefficient calculated.

The paper sample consists of six poets from different historical ages, and each poet has five poems. The method was programmed using the MATLAB program, the efficiency of the proposed method is 53% for the whole sample, and between 90% and 95% for each poet's poems.

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to